Transactions of the Chinese Society of Agricultural Engineering, the 1st in Agricultural Engineering, is supervised by China Association for Science and Technology, and sponsored by Chinese Society of Agricultural Engineering. It aims to introduce the latest scientific achievements and developing trends of Agricultural Engineering and provides the academic developments abroad and domestic of the discipline. The scope covers agricultural water-soil engineering, agricultural information and electrical technology, agricultural products processing engineering.
The journal is included in EI, JST, Pж(AJ), CA and CSCD.
Editor-in-Chief Zhu Ming
Deputy Editor-in-Chief Wei Xiuju Zhang Ruihong Xi Weimin Wang Liu Wang Yingkuan Li Pingping Ying Yibin Tong Jin Yun Wenju Zhao Chunjiang Kang Shaozhong
Extracting the crop lodging information, such as spatial location and area, is very critical to agricultural disaster assessment and agricultural insurance claim. It is hard work to measure the lodging information using the traditional methods such as ground survey. The survey method using remote sensing techniques can quickly and efficiently obtain the crop lodging information, but it is limited by the lack of timely and available satellite remote sensing data. In recent years, the application of unmanned aerial vehicles (UAV) develops rapidly in the agricultural field, which makes UAV equipped with image sensors become a portable, stable and efficient crop survey tool with the characteristics of low cost, high timeliness, and small weather impact. A few scholars have measured the lodging area of wheat and corn crops using visible or multi-spectral images. However, the studies using UAV multi-spectral images to survey cotton lodging information have not been published. Therefore, a survey method of cotton lodging using multi-spectral image was derived from the UAV remote sensing experiment which was carried out in the 135th Regiment of the 8th Division of Xinjiang Production and Construction Corps on August 23 of 2017. In this study, the spectral characteristics of lodging and normal cotton were first analyzed and summarized, and a series of vegetation indices were calculated. Sixteen texture features of the first two components were calculated according to gray level co-occurrence matrix (GLCM) after principal component analysis (PCA), and the optimal texture features were selected in terms of the coefficient of variation (CV) and the relative difference (RD). The result showed that it was apparently different between lodging and normal cotton in spectral curves and texture features. Compared with normal cotton, the difference in reflectance of the lodging cotton in the visible wavebands was small, while it was significant in the red and near-infrared bands, in which the reflectance dropped about 0.12–0.20. The main reason for this phenomenon might be the collapse of the cotton canopy structure. The mean of the first principal component (PCA1＿mean), PCA1＿entropy, PCA1＿homogeneity, PCA2＿mean, and PCA2＿homogeneity texture features had the lower CV and higher RD, which were very suitable for classification of normal and lodging cotton. Then, ten vegetation indices and five texture features of the measured samples were calculated as characteristic indexes, and the training set and test set were divided. Forward stepwise was used to select the best features on the data set. The binary Logistic models on lodging and normal cotton classification were constructed with different features combination, including spectral model, texture model, and spectral-texture model. The prediction accuracy of the classification models was evaluated by the ground survey samples. All classification models had a good classification effect on lodging and normal cotton. Among them, the texture model constructed with the PCA1＿mean had the highest precision, and the classification accuracy on the test set was 91.30%. The classification accuracy of spectral-texture model and spectral model was following, but the classification accuracy was also more than 85%. Finally, the classification models were applied to the multi-spectral image at the pixel level, and three thematic classification maps were created. Compared with the visual interpretation results, the texture model had the best classification effect. The “salt-and-pepper plaque” of the thematic map was the least, and the lodging crop had the characteristic of aggregation occurring in space. The ROC (receiver operating characteristic) curve was closest to the upper left corner and the calculated AUC (area under the ROC curve) value was 0.80. According to the results of the study, we may safely draw the conclusion that the method to extract cotton lodging information using the multi-spectral image of UAV remote sensing based on optimum texture features is accurate. The lodging classification has high accuracy of mapping, which is basically consistent with the actual lodging in the field.
At present, finding valuable application of rice husk should be targeted for further research, and how to deal with sewage sludge has become an issue that requires urgent attention. In this study, rice husk flour, an agricultural waste material, was used to condition sludge and enhance sludge dewaterability. The effect of rice husk flour dosage on the sludge dewaterability was investigated, and the surface element content, main components of rice husk flour and the microstructure of sludge cakes were investigated to analyze conditioning mechanisms. In addition, the effects of adding rice husk flour on the turbidity and the soluble chemical oxygen demand (SCOD) of sludge filtrate were also investigated, and the advantages of adding rice husk flour for future filtrate treatment were evaluated. The results showed that the dewaterability of sludge conditioned with the rice husk flour and FeCl
3 (138.09 g/kg dry solids, DS) was much superior to the sludge conditioned with rice husk flour, and the optimal dosage of rice husk flour was 70%. With the optimal rice husk dosage, the sludge specific resistance to filtration (SRF) decreased by 59.73%; the net sludge solids yield (
YN) increased by 45.27%; the solid content of sludge cake increased from 13.99% to 23.97%, in comparison with the sludge conditioned with FeCl
3 (138.09 g/kg) alone. When the rice husk flour was used to condition the sewage sludge combined with FeCl
3 (138.09 g/kg), the large cracks were found in the sludge cake easily by an environmental scanning electron microscope (ESEM) and the coefficient of compressibility of sludge cake was decreased to 0.92 (the coefficients of compressibility of raw sludge cake and sludge cake conditioned with FeCl
3 alone were 1.21 and 1.08, respectively). Accordingly, the sludge cake became more incompressible and permeable, and the sludge moisture could easily pass through. Therefore, the rice husk flour was proved to play a supportive role as a skeleton builder in the sludge cake for sludge conditioning and dewatering. The surface element contents and zeta potential of rice husk flour tested by an energy-dispersive spectrometry (EDS) and Zetasizer Nano analyzer showed that the stability of sludge colloidal system was not destroyed by charge neutralization, and the sludge particles could not congregate with each other under the treatment with rice husk flour alone. It might be the main reason why adding rice husk flour and FeCl
3 was superior to adding rice husk flour alone for sludge conditioning and dewatering. Moreover, adding rice husk flour could reduce the turbidity and SCOD of filtrate (the turbidity decreased from 11.89 NTU to 2.91 NTU and SCOD decreased from 664.87 to 79.93 mg/L, respectively) because the rice husk flour addition might adsorb the pollutants in sludge supernatant. As important indices of water quality, the reduction of turbidity and SCOD was benefited to further filtrate treatment because of the possible significant reduction of difficulty and cost. To be specific, adding rice husk flour as a conditioner aid can also improve the quality of filtrate for further filtrate treatment. Therefore, using rice husk flour to condition sludge is economically feasible and promising.
Xinjiang is a main producing area of cotton in China. This study investigated the effects of global warming and plastic mulching on cotton-planting zoning with different mature in Xinjiang. The climatic data were from 173 meteorological stations during 1960–2015 in temperate zone around Xinjiang within a range of 200 km. The digital elevation mode data were from the United States Geological Survey, which had the resolution about 900 m. We analyzed the spatio-temporal variation of accumulated temperature not less than 10 °C, frost-free period and mean temperature in July with the aid of ANUSPLIN interpolation software. The cotton-growing area was classified based on these three parameters. In addition, the change of planting boundaries and area of different cotton matures were studied with climate change and the compensation effect of plastic mulching. The main results included: 1) The accumulated temperature not less than 10 °C, frost-free period and mean temperature in July showed an increasing trend in 1960–2015. The regional differences of thermal resources were obvious in Xinjiang. The accumulated temperature not less than 10 °C, frost-free period and mean temperature in July were closely related to the terrain elevation. The thermal resources were richer in the southern Xinjiang than those in the northern Xinjiang and richer in plain areas than in mountain areas. 2) Under global warming, the ratio of planting areas of middle mature and early-middle mature cotton regions all increased. The area of middle mature cotton region increased by 3.82 × 10
4 km
2, and the main increase areas were located in the eastern part of Tarim Basin. The increased area of early-middle mature cotton was widely distributed in the eastern Junggar Basin, the southern Turpan Basin, the southern Hami Basin and the western Tarim Basin. However, the proportion of planting area of early mature cotton did not change significantly and the exceptional early-mature and unsuitable areas decreased. 3) The accumulated temperature not less than 10 °C and mean temperature in July were the main limiting factors in unsuitable planting areas, besides the areas near Tianshan, Altai and Kunlun Mountains were also restricted by frost-free period. The main thermal limiting factor in theearly-middle mature cotton region (Taha), early mature cotton region and most of exceptional early-mature region was the accumulated temperature not less than 10 °C. 4) Cotton plastic mulching had no significant influence on the planting boundaries of middle mature, early mature and unsuitable planting areas. However, it had a significant influence on the planting boundaries of cotton regions in the area of Junggar Basin. With plastic mulching, the planting boundary of the early-middle mature cotton extended 65 km to the east approximately, and that of the early mature cotton regions extended 0–300 km to the east. With plastic mulching, the planting area of early-middle mature cotton (Yeta) increased by 5.47 × 10
4 km
2, some of which was from the former Taha cotton area. In addition, the planting areas of the early mature and exceptional early-mature cotton decreased by 1.4% and 1.6% respectively. This study provided an effective method for cotton-planting zoning with different mature in Xinjiang.
The formation and evolution of soil salinization in the artificial oasis in the arid area is a complex process involving multiple factors, multi-level driving, and multi-process coupling. To reveal the spatial-temporal differentiation of water and salt in the arid pumping-irrigation district, this paper selected the 1st phase irrigation district of Jingtaichuan Electrical Pumping Irrigation District in Gansu Province, located at the edge of Tengger Desert, as the typical research area. A total of five index factors directly driving differentiation of water and salt on a regional scale in 1994, 2001, 2008, and 2015, such as surface salt, soil salinity, groundwater salinity, surface irrigation amount, and groundwater depth were selected. We determined the weight of each index factor by the extension analytic hierarchy process. With the help of monitoring classification and spatial analysis technology in ArcGIS software, the spatial distribution raster maps of each index factor were obtained, and each raster map was standardized, after which the raster map was spatially nested and superimposed according to the weight of each index factor and the spatial-temporal differentiation of water and salt on a regional scale was quantitatively analyzed. The results showed that 1) The weight of each index factor affecting the spatial-temporal differentiation process of water and salt on a regional scale was ranked as follows: groundwater depth (0.319 0) > groundwater salinity (0.271 0) > soil salinity (0.197 1) > surface salinity (0.174 8) > surface irrigation (0.038 1). Groundwater depth and groundwater salinity were the main driving factors affecting the spatial-temporal differentiation of water and salt at a regional scale. 2) The saline land in the study area was mainly distributed in the eastern closed hydro-geological units. Overall, the area of mild saline land was the largest, accounting for 7.22%–11.12%, followed by the moderate saline land, accounting for 3.19%–5.72%; the area of heavy saline land was the smallest, accounting for 3.03%–4.91% during 1994–2015. The saline land in the study area was still in the process of development and showed an accelerating growth trend. Among them, the development speed was mild saline land area > the moderate saline land > the heavy saline land. 3) The spatial-temporal distribution of water and salt in the study area was related to the overall topography. The distribution of total water-salt equivalent value was low in the west and high in the east, increasing from southwest to northeast in the arc diffusion development trend, affected by the natural geomorphology and topographic conditions. With the passage of time, the total could be divided into two stages, i.e., a stable development period (1994–2008) and a rapid development period (2008–2015). Affected by the continuous expansion of the regions with higher total water and salt content in the east to the west, the security of farmland resources in the west was potentially threatened, and the overall development trend of water and salt in the study area was not conducive to the sustainable development of agricultural production in the irrigated areas. Based on the analysis of single driving factors, this study proposed an important means for coupling and superimposing multiple driving factors, which provided a new visualization for the comprehensive development of the spatial-temporal differentiation of water and salt in the study area. It could provide a useful reference for studying the development trend of the spatial-temporal differentiation process of water and salt on a regional scale.
